diffray

About diffray

diffray is a next-generation AI-powered code review platform designed to eliminate the noise and ineffectiveness of traditional single-model AI tools. It employs a sophisticated multi-agent architecture, where over 30 specialized AI agents each focus on a distinct domain such as security vulnerabilities, performance bottlenecks, bug patterns, best practices, and even SEO. This targeted approach allows diffray to conduct deep, contextual investigations into your code changes rather than offering generic, speculative suggestions. The platform is codebase-aware, meaning it analyzes pull requests within the full context of your repository's existing code, architecture, and historical decisions. This results in highly actionable, precise feedback that developers can immediately use to improve their code. diffray is built for development teams of all sizes who are frustrated with false positives and missed critical issues, aiming to drastically reduce PR review time—from an average of 45 minutes to just 12 minutes per week—while significantly improving code quality and security. It integrates seamlessly with GitHub, GitLab, and Bitbucket, offering a free plan for open-source projects and a straightforward trial for private repositories.

Features of diffray

Multi-Agent Specialized Architecture

Unlike monolithic AI tools, diffray deploys a team of over 30 specialized agents, each an expert in a single domain such as security, performance, concurrency, or code duplication. This division of labor ensures deep, focused analysis. For example, the security agent is trained specifically to spot injection vulnerabilities and insecure dependencies, while the performance agent looks for inefficient loops or memory leaks. This specialization is the core reason diffray achieves an 87% reduction in false positives and catches three times more real issues, as each agent applies expert-level scrutiny to its dedicated area.

Full Codebase Context Awareness

diffray moves beyond analyzing just the diff in a pull request. It intelligently examines the entire repository to understand project context, existing patterns, and past decisions. This allows it to catch issues like duplicate utility functions, type drift between files, or the introduction of redundant libraries (e.g., adding moment-timezone when dayjs is already in use). It can trace function call impacts across the codebase and identify tests that don't actually assert anything, providing feedback that is relevant and specific to your project's unique environment.

Actionable and Clean Feedback

diffray is designed for developer productivity, delivering comments that are clear, direct, and immediately useful. It avoids emoji spam and vague suggestions, instead providing concrete file paths, line numbers, and specific remediation steps. For instance, it won't just say "consider updating callers"; it will list the exact three call sites with type mismatches and note which tests need updates. This clarity leads to a 98% developer action rate, as the feedback is trustworthy and easy to act upon, eliminating time wasted on deciphering noisy or irrelevant comments.

Seamless Integration and Easy Setup

Getting started with diffray requires minimal configuration. Developers can sign in directly with their GitHub account, install the diffray GitHub App with a few clicks, and select which repositories to enable. The platform respects your control, allowing customization of review settings and enabling specific agents based on team needs. Once configured, it automatically provides intelligent reviews on new pull requests within minutes, requiring no ongoing maintenance or complex pipeline adjustments to deliver consistent value.

Use Cases of diffray

Accelerating Pull Request Reviews for Engineering Teams

Development teams burdened by lengthy manual code reviews can use diffray to automate the initial screening process. By catching common bugs, security flaws, and consistency issues early, diffray allows human reviewers to focus on higher-level architecture, design, and business logic. This shifts the team's effort from finding basic issues to discussing complex solutions, effectively cutting average PR review time from 45 minutes to just 12 minutes per week and accelerating overall development velocity without sacrificing code quality.

Enforcing Code Consistency and Preventing Tech Debt

For growing codebases, maintaining consistency and preventing duplication is a constant challenge. diffray acts as a vigilant guardian against tech debt by identifying duplicate utility functions, drifting type definitions, and reimplemented validation logic. It suggests consolidating code into shared schemas or utilities, ensuring the codebase remains clean, maintainable, and scalable as the team and project evolve, which is especially critical for Series B and later-stage companies.

Enhancing Security and Reliability in Critical Applications

Fintech, healthcare, and other security-sensitive industries require rigorous code scrutiny. diffray's specialized security and data integrity agents are adept at finding critical issues that generic tools miss, such as non-atomic database updates, SQL injection vectors, and concurrency race conditions. By providing actionable findings on these high-stakes problems, diffray helps engineering teams build more reliable and secure applications, directly supporting compliance and risk management goals.

Improving Code Quality in Open Source Projects

Open source maintainers often face a high volume of contributions with varying quality. diffray's free tier for open-source projects provides these maintainers with a powerful, automated first-pass review tool. It helps contributors adhere to project standards, catch common bugs before merge, and reduce the maintenance burden on core team members by ensuring incoming code is vetted for best practices, context-awareness, and potential issues, leading to healthier and more sustainable open-source ecosystems.

Frequently Asked Questions

How does diffray differ from other AI code review tools?

diffray fundamentally differs through its multi-agent architecture. Traditional tools use a single, general-purpose AI model that often produces noisy, generic feedback. diffray uses over 30 specialized agents, each an expert in a specific domain like security or performance. This allows for deep, investigative analysis of your code within the full context of your repository, leading to far fewer false positives, more real issues caught, and highly actionable comments that developers actually use.

Is my source code stored or used for training?

No, diffray prioritizes security and privacy. Your source code is never stored long-term or used to train AI models. The platform operates on a strict principle of analyzing code only for the duration of the review to provide feedback. It is also compliant with SOC 2 infrastructure standards and GDPR, ensuring that your intellectual property remains secure and within your control at all times.

Can I customize which agents review my code?

Yes, diffray offers full configurability. During setup, you can choose which specialized agents to enable for your repository based on your team's priorities. For instance, you might enable the security, performance, and bug-detection agents while disabling the SEO agent for an internal API project. This allows you to tailor the review focus to your specific tech stack and quality goals.

What platforms does diffray integrate with?

diffray offers seamless integration with major Git hosting platforms. It provides a dedicated GitHub App for easy installation and also supports GitLab and Bitbucket. For organizations with specific infrastructure requirements, diffray offers an on-premise deployment option, giving teams flexibility in how they integrate the tool into their existing development workflow and security policies.